This library provides a number of common functions and types useful
in statistics. We focus on high performance, numerical robustness,
and use of good algorithms. Where possible, we provide
references to the statistical literature.

The library's facilities can be divided into four broad categories:

Working with widely used discrete and continuous probability
distributions. (There are dozens of exotic distributions in use;
we focus on the most common.)

Type class for generating random variates for given distribution
is added.

Modules Statistics.Math and Statistics.Constants are moved to
the math-functions package. They are still available but marked
as deprecated.

Changed in 0.10.0.1

dct and idct now have type Vector Double -> Vector Double

Changes in 0.10.0.0:

The type classes Mean and Variance are split in two. This is
required for distributions which do not have finite variance or
mean.

The S.Sample.KernelDensity module has been renamed, and
completely rewritten to be much more robust. The older module
oversmoothed multi-modal data. (The older module is still
available under the name S.Sample.KernelDensity.Simple).

Histogram computation is added, in S.Sample.Histogram.

Forward and inverse discrete Fourier and cosine transforms are
added, in S.Transform.

Root finding is added, in S.Math.RootFinding.

The complCumulative function is added to the Distribution
class in order to accurately assess probalities P(X>x) which are
used in one-tailed tests.

A stdDev function is added to the Variance class for
distributions.

The constructor S.Distribution.normalDistr now takes standard
deviation instead of variance as its parameter.

A bug in S.Quantile.weightedAvg is fixed. It produced a wrong
answer if a sample contained only one element.

Bugs in quantile estimations for chi-square and gamma distribution
are fixed.

Integer overlow in mannWhitneyUCriticalValue is fixed. It
produced incorrect critical values for moderately large
samples. Something around 20 for 32-bit machines and 40 for 64-bit
ones.

A bug in mannWhitneyUSignificant is fixed. If either sample was
larger than 20, it produced a completely incorrect answer.

One- and two-tailed tests in S.Tests.NonParametric are selected
with sum types instead of Bool.

Test results returned as enumeration instead of Bool.

Performance improvements for Mann-Whitney U and Wilcoxon tests.

Module S.Tests.NonParamtric is split into S.Tests.MannWhitneyU
and S.Tests.WilcoxonT

sortBy is added to S.Function.

Mean and variance for gamma distribution are fixed.

Much faster cumulative probablity functions for Poisson and
hypergeometric distributions.

Maintainer's Corner

Readme for statistics-0.10.3.1

Statistics: efficient, general purpose statistics

This package provides the Statistics module, a Haskell library for
working with statistical data in a space- and time-efficient way.

Where possible, we give citations and computational complexity
estimates for the algorithms used.

Performance

This library has been carefully optimised for high performance. To
obtain the best runtime efficiency, it is imperative to compile
libraries and applications that use this library using a high level of
optimisation.